kde.h

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#ifndef CMP_KDE_H
#define CMP_KDE_H
 
#include <cmp_defines.h>
#include <statistics.h>
#include <kernel++.h>
#include <optimization.h>
#include <distribution.h>
 
 
namespace cmp::density {
 
// Here we implement a KDE class that uses the above bandwidth and kernel classes
class KDE {
  private:
    std::shared_ptr<kernel::Bandwidth> bandwidth_{nullptr}; 
    std::shared_ptr<kernel::Kernel> kernel_{nullptr};       
 
    // Owning or non-owning data storage
    Eigen::MatrixXd data_{0, 0};                             
    std::optional<Eigen::Ref<const Eigen::MatrixXd>> pData_; 
    bool isOwning_{false};                                   
 
    // Dimension and number of points
    size_t dim_{0};                                          
    size_t nPoints_{0};                                      
  public:
 
    KDE();
 
    KDE(std::shared_ptr<kernel::Bandwidth> bandwidth, std::shared_ptr<kernel::Kernel> kernel);
 
    // Copy and move constructors
    KDE(const KDE &other);
    KDE(KDE &&other) noexcept;
 
    // Copy and move assignment operators
    KDE &operator=(const KDE &other);
    KDE &operator=(KDE &&other) noexcept;
 
    void set(const std::shared_ptr<kernel::Bandwidth> &bandwidth, const std::shared_ptr<kernel::Kernel> &kernel);
 
    void condition(const Eigen::Ref<const Eigen::MatrixXd> &data, bool copyData = false);
 
    double eval(const Eigen::VectorXd &x) const;
 
  public:
    enum class BandWidthSelectionMethod {
        SCOTT,
        SILVERMAN
    };
 
};
 
Eigen::MatrixXd bandwidthSelectionRule(const KDE::BandWidthSelectionMethod &method, Eigen::Ref<Eigen::MatrixXd> xObs);
 
void bandwidthOptimizationCrossValidation(const cmp::statistics::KFold& kf, Eigen::Ref<Eigen::MatrixXd> xObs, std::shared_ptr<cmp::kernel::Kernel> kernel, std::shared_ptr<cmp::kernel::Bandwidth> initialBandwidth, const double &min, const double &max, nlopt::algorithm alg, const double & tol = 1e-4);
 
 
 
} // namespace cmp::density
 
#endif // CMP_KDE_H